The Future of Forecasting: Technology Promises Faster Weather Predictions on a Smaller Scale

By Sumner, Thomas | Science News, May 2, 2015 | Go to article overview

The Future of Forecasting: Technology Promises Faster Weather Predictions on a Smaller Scale


Sumner, Thomas, Science News


In late January, a massive snowstorm drifted toward New York City. Meteorologists warned that a historic blizzard could soon cripple the Big Apple, potentially burying the city under 60 centimeters of snow overnight. Governor Andrew Cuomo took drastic action, declaring a state of emergency for several counties and shutting down the city that never sleeps. For the first time in its 110-year history, the New York City Subway closed for snow.

As the hours wore on, however, the overhyped snowfall never materialized. The storm hit hard to the east but just grazed the city with a manageable 25 centimeters of fresh powder. When Cuomo took grief for overreacting, many meteorologists sympathized. A meteorological misjudgment of just a few minutes or miles can mislead officials, trigger poor decisions and bring on public jeers. But underestimating a storm's impact may put people in peril. The answer is to make weather forecasts more precise, both in time and space.

Unfortunately, that's exceedingly difficult. Despite years of improvements in predictions, weather gurus may never be able to deliver accurate daily forecasts further ahead than they can now. So they're switching gears. Instead of pushing predictions further into the future, they are harnessing technology to move weather forecasting into the hyperlocal.

By incorporating clever computing, statistical wizardry and even smartphones, future forecasts may offer personalized predictions for areas as narrow as 10 Manhattan city blocks over timescales of just a few minutes. The work could one day provide earlier warnings for potentially deadly storms and even resolve personal conundrums such as whether to grab an umbrella for a run to the coffee shop or to wait a few minutes because the rain will soon let up.

"We're entering a promising era for small-scale forecasting," says meteorologist Lans Rothfusz of the National Oceanic and Atmospheric Administration's National Severe Storms Laboratory in Norman, Okla. "The sky's the limit, no pun intended."

Atmospheric chaos

Weather is so complex that to predict it with any precision, forecasters need robust information about what the weather is doing right now. A worldwide battalion of planes, ships, weather stations, balloons, satellites and radar networks streams details of nearly every facet of the atmosphere to meteorologists. "In the meteorology business, we'll take all the data we can get," Rothfusz says.

Measurements such as atmospheric pressure, temperature, wind speed and humidity feed into data assimilation software that compiles a 3-D reconstruction of the atmosphere. Where no measurements exist, the software uses nearby data to intelligently fill in the gaps. Once the reconstruction is complete, the computer essentially presses fast-forward. Numerical calculations simulate the future behavior of the atmosphere to predict weather conditions hours or days in advance. For instance, a rising pocket of moist, warm air might be expected to condense into a storm cloud and be blown from an area with high atmospheric pressure to a low-pressure region.

The goal is to provide a useful, or "skilled," prediction. A forecast is said to have skill if its prediction is more accurate than the historical average for that area on that date. Even using cutting-edge supercomputers and a global network of weather stations, meteorologists can provide a skilled forecast only three to 10 days into the future. After that, the computer typically becomes a worse predictor than the historical average.

Many meteorologists believe this limitation won't be significantly improved on anytime soon. The problem, they say, stems from proverbial seabirds (or butterflies, depending on the story's telling). In 1961, mathematician and meteorologist Edward Lorenz discovered that small changes in the initial conditions of a weather system, when played out over a long enough period of time, can yield wildly different outcomes. …

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